Evidence map›Paper›PMID 42742291›Full record

ArticleBriefings in bioinformatics2026

bioETH-PRS: confidential polygenic risk scoring with smart contracts on an FHE-enabled blockchain.

Kimon Antonios Provatas, Christos Galanopoulos, Ilias Georgakopoulos-Soares

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kimon Antonios ProvatasDivision of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Dell Pediatric Research Institute, Austin, TX 78712, United States.
Christos GalanopoulosDivision of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Dell Pediatric Research Institute, Austin, TX 78712, United States.
Ilias Georgakopoulos-SoaresDivision of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Dell Pediatric Research Institute, Austin, TX 78712, United States.

Funding

Harnessing the Power of Kmers: Concepts and Methods for Genomic and Proteomic ResearchR35GM155468 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI Ilias Georgakopoulos-Soares · 2024 to 2026
$1.2M
National Institute of General Medical Sciences of the National Institutes of Health R35GM155468NIGMS NIH HHS R35 GM155468
6 · The paper itself

Abstract

Polygenic risk scores (PRSs) aggregate genetic effect estimates to predict disease susceptibility, yet calculating one through an external service can require exposing raw genotype data. Homomorphic encryption hides those data during the calculation but, in prior work, still places a designated evaluator in a position of trust. We present bioETH-PRS, a protocol that replaces the evaluator with publicly auditable smart contracts on a blockchain supporting Fully Homomorphic Ethereum Virtual Machine (fhEVM). Using integer-exact encrypted arithmetic, bioETH-PRS computes the PRS dot product entirely in the encrypted domain, so genotype dosages and, at the model provider's discretion, the GWAS weights stay hidden from the parties performing the computation. A fixed-point encoding represents signed weights as nonnegative integers within a bound that rules out overflow, recovering the score to the precision of the published weights. A four-contract architecture separates data custody, model publication, computation, and output release, and supports both a classic path that stores encrypted inputs and an appreciably cheaper streaming path that discards them. A release oracle can return a randomized risk category instead of the raw score, limiting what a repeated querier learns. Prototype evaluation on real GWAS fixtures, including a run on a public testnet, shows cost growing linearly with variant count and suggests the approach may be practical where transaction fees are low. Trust is redistributed rather than removed: the system still depends on the contracts, the blockchain, and the fhEVM services. We evaluate additive models of moderate size, not genome-wide or clinical use.

Indexed as

BlockchainMultifactorial InheritanceContractsGenetic Risk ScoreGenome-Wide Association StudyHumansblockchainFHEgenomic privacyrisk categoriessmart contracts

Identifiers

PMID42742291
PMCPMC13575936

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.